ArticleGlobal & regional health technology assessment
Exploring the current and future role of artificial intelligence in pharmaceutical market access: insights from a European survey.
Article in Global & regional health technology assessment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Artificial Intelligence (AI) is rapidly expanding across the pharmaceutical value chain; however, empirical evidence on its application in Market Access (MA) remains limited. Given the strategic relevance and regulatory complexity of MA, understanding current AI adoption and perception represents a significant evidence gap. This study provides one of the first exploratory, European-focused assessments specifically investigating the role of AI in pharmaceutical MA. Methods: A structured, closed survey was conducted among European pharmaceutical MA executives and senior leaders. The questionnaire investigated AI adoption levels, governance and implementation models, perceived benefits and barriers, and current and future applications, with a focus on MA activities. The survey was distributed between June and November 2025 through targeted professional outreach and conference-based data collection. Results: Fifty responses were collected. Overall, 44% of respondents reported structural AI implementation within their organizations, with MA being the most impacted function (59%), contrasting with previous analyses where MA was among the least affected areas. AI adoption was strongly linked to company size, favoring large companies. Key barriers to AI adoption in MA included limited availability of high-quality data, data integration challenges, lack of internal expertise, and regulatory uncertainty. Reported benefits were mainly operational, while respondents identified strong future potential in market analysis, forecasting, health economics and outcomes research, and pricing and reimbursement strategy. Conclusions: AI is increasingly perceived as a valuable enabler in MA, although adoption remains heterogeneous and at an intermediate maturity stage. Effective integration requires robust governance, regulatory clarity, and AI-generated insights that support-rather than replace-human expertise.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.